ABSTRACT
Identifying air pollution sources is critical for developing mitigation strategies to protect human health. Many cities
in the western United States experience elevated short-term PM2.5, composed of heterogeneous PM2.5 mixtures that
vary seasonally. PM2.5 is a mixture of primary PM2.5 (aerosols emitted directly from a source) and secondary PM2.5
(aerosols formed in the atmosphere from reactions involving primary pollutants, precursor emissions, and atmospheric
processes). Although source apportionment models can be applied to trace pollutants back to their emission sources, all
conventional source apportionment models share a common limitation: only the primary PM2.5 is apportioned.
Meteorology plays a significant role in elevated air pollution concentrations during colder months in the western
U.S. Under typical meteorological conditions, temperature decreases as altitude increases. During an inversion, this
relationship is inverted – warm air is held above cooler air – causing ambient air pollutants, such as PM2.5, to be trapped
near ground level. Several major historical air pollution events, including the 1952 London “Great Smog,” were caused
by inversions. During colder months in the western U.S., it is common for over 80% of the total PM2.5 to be secondary
PM2.5. To create effective regulations to protect human health in these cities, air quality managers must understand
the origin of secondary PM2.5. Given the predominance of secondary PM2.5 during colder months, existing source
apportionment models cannot reliably identify which source(s) should be prioritized for mitigation strategies.
We propose to address this public health problem by developing an innovative air quality model that apportions
both primary and secondary PM2.5, and to use the estimates from this model in a large 12-city epidemiologic study.
We will develop a new data fusion method that combines air quality model results and speciated PM2.5 observations to
create seasonal, location-specific source profiles for both primary and secondary PM2.5 species. These new source
profiles will be used in a multi-year source apportionment model to estimate daily PM2.5 source concentrations during
colder months for Boise, Salt Lake City, Provo, Ogden, Denver, Reno, Las Vegas, Sacramento, Fresno, Modesto,
Bakersfield, and Visalia. Emergency department visit data from these cities will be used to estimate associations
between the PM2.5 source concentration estimates and cardiorespiratory emergency visits.
Our project directly addresses major limitations in existing source apportionment approaches by developing
methods to apportion secondary PM2.5. Our multicity epidemiologic analyses will uniquely contribute to the literature by
providing source-specific health associations that comprehensively account for both primary and secondary PM2.5
originating from a given source. We focus on the significant public health problem of PM2.5 in western U.S. cities prone
to inversions and accompanying PM2.5 spikes, but our novel source apportionment methodologies can be readily applied
to other regions and studies. Findings from our study will be of immediate interest to air quality and public health
stakeholders, informing policy development to reduce high pollution days and protect public health.
